Effect of plasma chemistry on the simulation of helium atmospheric-pressure plasmas

The effect on the selection of different plasma chemistries for simulating a typical dielectric barrier discharge (DBD) driven by quasi-pulsed power source (20 kHz) is investigated. The numerical simulation was performed by using the one-dimensional self-consistent fluid modeling solver. Our simulation result indicates that the computed temporal current density can be significantly improved by using a complex version of plasma chemistry module rather than the simple one and demonstrates an excellent agreement with the experimental data. The result suggests the metastable, excited and ionic helium related reaction channels, which are important in simulating a DBD, should be taken into account. Furthermore, it also reveals that the power absorption of ions is considerably higher than that of the electron.     

Entropic component analysis and its application in geological data

We present an entropic component analysis for identifying key parameters or variables and the joint effects of various parameters that characterize complex systems. This approach identifies key parameters through solving the variable selection problem. It consists of two steps. First, a Bayesian approach is utilized to convert the variable selection problem into the model selection problem. Second, the model selection is achieved uniquely by evaluating the information difference of models by relative entropies of these models and a reference model. We study a geological sample classification problem, where a brine sample from Texas and Oklahoma oil field is considered, to illustrate and examine the proposed approach. The results are consistent with qualitative analysis of the lithology and quantitative discriminant function analysis. Furthermore, the proposed approach reveals the joint effects of the parameters, while it is unclear from the discriminant function analysis. The proposed approach could be thus promising to various geological data analysis.     

Comparison of image reconstruction by using near‐field and far‐field data for an imperfect conductor

Image reconstruction by using near‐field and far‐field data for an imperfectly conducting cylinder is investigated. A conducting cylinder of unknown shape and conductivity scatters the incident wave in free space and the scattered near and far fields are measured. By using measured fields, the imaging problem is reformulated into an optimization problem and solved by the genetic algorithm. Numerical results show that the convergence speed and final reconstructed results by using near‐field data are better than those obtained by using far‐field data. This work provides both comparative and quantitative information. © 2001 John Wiley & Sons, Inc. Int J RF and Microwave CAE 11: 69–73, 2001.     

Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

The Internet is a hierarchical architecture comprising heterogeneous entities of privately owned infrastructures, where higher level Internet service providers (ISPs) supply connectivity to the local ISPs and charge the local ISPs for the transit services. One of the challenging problems facing service providers today is how the profitability can be increased while maintaining good service qualities as the network scales up. In this work, we seek to understand the fundamental issues on the "interplay" (or interaction) between ISPs at different tiers. Although the local ISPs (which we term peers) can communicate with each other by purchasing the connectivity from transit ISPs, there stands an opportunity for them to set up private peering relationships. Under this competitive framework, we explore the issues on 1) the impact of peering relationship; 2) resource distribution; 3) revenue maximization; and 4) condition for network upgrade. First, a generalized model is presented to characterize the behaviors of peers and the transit ISP, in which their economic interests are reflected. We study how a peer can distributively determine its optimal peering strategy. Furthermore, we show how a transit ISP is able to utilize the available information to infer its optimal pricing strategy, under which a revenue maximization is achieved. Two distributed algorithms are proposed to help ISPs to provide a fair and efficient bandwidth allocation to peers, avoiding a resource monopolization of the market. Last, we investigate the above issues in a "many-peers region," that is, when we scale up the network. We provide insightful evidence to show that the ISPs can still gain profits as they upgrade the network infrastructures. Extensive simulations are carried out to support our theoretical claims.     

Dynamically adjusting MPEG4 video streams based on network bandwidth

In the paper, we try to find a method that can service more users in a video-on-demand (VoD) system, based on MPEG-4 object streams. The characteristics of object segmentation made on MPEG-4 videos can be utilized to reduce re-transmission of the same objects, and then the saved bandwidth can be used to service more users. However, some thresholds must be analyzed first to maintain the acceptable quality of services (QoS) requested by users, when reducing unnecessary object transmission on one side. Thus, according to the defined thresholds, we propose a dynamically adjusting algorithm to coordinate the object streams between the server and clients. The server not only allocates network bandwidth, but also adjusts ever-allocated QoS appropriately using a degrading and upgrading strategy, based on the current network status. Lastly, through the simulation, we found that our method has better performance than the other three methods owing to its flexibility to the network status.

Secretome analysis of novel IgE-binding proteins from Penicillium citrinum

The Penicillium genus of fungi is a frequently reported cause of allergic reactions. However, only a limited number of allergens have been reported. In Penicillium spp., many allergens show higher IgE-binding activity in culture filtrate extracts than in cellular extracts. In order to investigate the IgE-reactive profile of mold-sensitized patients, secreted IgE-reactive proteins from Penicillium citrinum were identified by 2-DE, serum immunoblotting, and nanoLC-MS/MS. Among the IgE-reactive spots, one known allergen, Pen c 13, and four novel allergens were identified. The cDNAs coding for Pen c 32 and Pen c 30 were cloned using designed primers based on nanoLC-MS/MS analysis. The amino acid sequences of Pen c 32 and Pen c 30 were, respectively, found to have extensive similarity with those of pectate lyases and catalases from various fungi. Native Pen c 30 was shown to have catalase activity and to bind to serum IgE from 48% of mold-allergic patients and induced immediate type skin reactions in a sensitized patient. Here, we present a proteome approach which resulted in the identification of four novel secreted allergens. These novel allergens might be useful in allergy diagnosis and in the treatment of mold-allergic disorders.     

Joint optimization of word alignment and epenthesis generation for Chinese to Taiwanese sign synthesis

This work proposes a novel approach to translate Chinese to Taiwanese sign language and to synthesize sign videos. An aligned bilingual corpus of Chinese and Taiwanese sign language (TSL) with linguistic and signing information is also presented for sign language translation. A two-pass alignment in syntax level and phrase level is developed to obtain the optimal alignment between Chinese sentences and Taiwanese sign sequences. For sign video synthesis, a scoring function is presented to develop motion transition-balanced sign videos with rich combinations of intersign transitions. Finally, the maximum a posteriori (MAP) algorithm is employed for sign video synthesis based on joint optimization of two-pass word alignment and intersign epenthesis generation. Several experiments are conducted in an educational environment to evaluate the performance on the comprehension of sign expression. The proposed approach outperforms the IBM Model2 in sign language translation. Moreover, deaf students perceived sign videos generated by the proposed method to be satisfactory     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Noise of He-Cd laser and its suppression

Linear relations have been observed between the reciprocal of the noise ratio and the reciprocal of the output power of the He-Cd laser as well as between the noise ratio and the net gain within the laser cavity. By a feedback method with an acoustooptic modulator in the laser cavity at the Brewster angle for low optical loss, a stable laser with high power output and low noise has been obtained. The noise ratio and the output power are 0.8% and 33 mW, respectively, at 4416 A     

Cooperative private searching in clouds

With the increasing popularity of cloud computing, there is increased motivation to outsource data services to the cloud to save money. An important problem in such an environment is to protect user privacy while querying data from the cloud. To address this problem, researchers have proposed several techniques. However, existing techniques incur heavy computational and bandwidth related costs, which will be unacceptable to users. In this paper, we propose a cooperative private searching (COPS) protocol that provides the same privacy protections as prior protocols, but with much lower overhead. Our protocol allows multiple users to combine their queries to reduce the querying cost while protecting their privacy. Extensive evaluations have been conducted on both analytical models and on a real cloud environment to examine the effectiveness of our protocol. Our simulation results show that the proposed protocol reduces computational costs by 80% and bandwidth cost by 37%, even when only five users query data.